Dynamics of Civil Structures, Volume 2

Elastomeric isolators are special devices used for seismic isolation of structures. Typically, they are made of alternate layers of steel and rubber and they positioned between the structure and its foundations to decouple them. Novel Graphene-Reinforced Elastomeric Isolators, GREI, are proposed in this study to overcome the heavy weight and long manufacturing process of elastomeric isolators currently used.

This manuscript presents an experimental dynamic analysis on rubber pads reinforced with a few layer graphene. Experimental modal analysis is performed on a mass-spring-damper system and the dynamics of the system and the mechanical properties essential to characterize the specimens are extracted from the measured frequency response function.

Results show that a few layer graphene transferred on a rubber pad increase stiffness and damping of the graphene-rubber composite; hence natural rubber can be used in lieu of high-damped rubber, saving the cost of reinforcing rubber with particulate fillers. Also results show that the mechanical properties of the graphene-rubber composite alter when varying the thickness of a few layer graphene transferred on rubber pads.

Rollercoasters are challenging structures. Although the ever-changing geometry can guarantee a thrilling ride, the complexity of loading patterns due to the intricate geometry make testing and analysis of these structures challenging. Fatigue-induced damage is one of the most common types of damage experienced by civil engineering structures subjected to cyclic loading such as bridges and rollercoasters. Fatigue cracking eventually occurs when structures undergo a certain number of loading and unloading recurrences. This cyclic loading under stresses above a certain limit induces microcracking that can eventually propagate into failure of a member or connection. Because of the geometric and structural similarities between rollercoasters and bridge connections, similar techniques can be used for structural health monitoring and estimation of remaining fatigue life. Uniaxial fatigue analysis methods are widely used for the analysis of bridge connections. However, there is little guidance for the analysis of complex connections. They can experience variable amplitude, multiaxial, and non-proportional loading. In such cases uniaxial fatigue methods are insufficient and can lead to underestimates. A framework for the understanding and analysis of multiaxial fatigue damage using strain data collected from strain rosettes is presented. Uniaxial and multiaxial fatigue analysis methods proposed for non-proportional loading are compared. Methods proposed are applicable to both rollercoaster and bridge connections. The critical plane method is used for the estimation of multiaxial fatigue life. Results show that non-proportional loading and the accuracy of the critical plane estimation can cause a significant decrease in the estimates of remaining fatigue life. This methodology is anticipated to be used for real-time fatigue prognosis and evaluation tools for bridge networks.

During the last two decades development of mobile/telecoms technologies has meant an increased number of antennas anywhere we are in order to be always connected. In addition, the forthcoming implementation of 5G networks will require the use of bigger and heavier antenna-equipment which would compromise the structural integrity of current structures. Between all the existing types in the market, Monopoles are sensitive and vulnerable structures in this sense, since the dynamics induced by the tip-lumped mass increment, the slenderness and increasing loading due to higher wind resistances would dare the current knowledge and more exhaustive analyses of stiffness and damping in fatigue and other matters like vortex shedding will be necessary. Nonlinear behaviour has already been found in the dynamic response of several monopoles under demanding operational conditions.

This paper presents a technique for the extraction of backbone curves from field tests using quick external Pull and Release excitation on calm weather conditions. Backbone curves are useful to set a vision around the behaviour of nonlinear systems with significant information about any coupling between the primary linear modes in their response. Decaying acceleration records, obtained following tuned steady-state oscillation of actual monopole owned by Arqiva, one of the biggest telecom-structures portfolio in the UK, are processed to estimate the instantaneous frequency, the envelope amplitude of the structural response and the physical behaviour of structural damping, thus extracting the monopole’s characteristic backbone curve. Results obtained from those analyses considering several types, geometries and boundary conditions demonstrate the implication of numerous non-linearities sources on the system. Soil-Foundation influence and connections frictions at different levels are able to determine completely the behaviour and modify with high impact the current standards and methodologies in structural engineering.

Floor motions can disturb occupants, leading to frequent complaints and loss of functionality. In especially vibration-sensitive facilities, this issue can be more critical, as high-resolution imaging equipment with stringent vibration criteria are often employed. As urban intensification increases, new buildings are being constructed in close proximity to existing vibration sources, such as rail lines and industrial facilities. While a number of vibration mitigation options are feasible to properly isolate these sensitive facilities, vibration trenches can provide a cost-effective solution if the space is available to allow its installation.

In this paper, three case studies are presented of buildings that required trenches to mitigate ground-borne vibration. The first is an office building that was to be located directly adjacent to a currently unused rail line. The owners were concerned that at some point in the future, the line would be reactivated, and wanted to address the potential issue proactively. A hollow open trench was designed which could be implemented in the future. The second project involved a performing arts centre located in close proximity to a rail switching line. Measurements on site indicated that ground-borne vibrations were likely to cause audible rumbles in the theatre. A solid concrete trench was designed to run parallel to the tracks along the property line to mitigate the vibrations. The third project involved an existing industrial facility that had recently installed a new stamping press. The facility was located adjacent to a row of residential single-family dwellings. Two parallel foam-filled trenches were designed and installed to address the ground-borne impulsive vibrations. Validation testing was completed which indicated close agreement with the modelled vibration attenuation.

In vibration-based structural health monitoring the natural frequencies of the monitored structures are subjected to different sources of change including: (i) varying environmental conditions (i.e., temperature, humidity, and wind conditions) and (ii) structural degradation and damage. Thus, an accurate detection of structural degradation and damage depends on removing any influence from the environmental conditions on the natural frequencies. If such an influence is not removed, there is a risk of false positive or negative damage diagnosis and thus the damage detection is not robust and reliable. In this study, removal of the environmental conditions and the following damage detection are conducted by applying an output-only principal component analysis as well as an input-output multi linear regression model. The purpose of this study is to assess robustness of these methods by highlighting their advantages and disadvantages in terms of modeling the environmental conditions and detecting structural changes. The investigation is based on vibration data of a wooden mast structure subjected to natural loads and induced with damage at different levels.

Drive-by Health Monitoring (DBHM) is a relatively new mobile health monitoring strategy that employs vehicle mounted sensors to monitor the health of bridge systems in an efficient and economical manner. Before DBHM can be realized as a viable health monitoring strategy, however, an approach for managing environmental and operational noise needs to be developed. In traditional health monitoring, machine learning techniques, such as neural networks, have been shown to reduce the effect environmental and operational noise has on damage detection accuracy; though, these methods typically require training on damage data, which can be difficult if not impossible to obtain for healthy structures. To resolve this issue, the authors proposed a methodology that utilizes a neural network architecture trained on realistic vehicle-bridge simulations to detect damage in physical highway bridges. For a simulation trained neural network to be able to detect physical bridge damage, numerical models must be able to accurately represent the behavior of a system when damaged. Therefore, the motivation of this work is to identify and validate physics-based techniques for modeling damage induced fluctuations in the dynamic response of highway bridge structures. This study focuses on one of the most common types of bridge damage, frozen support bearings. The authors introduce methods for modeling frozen bearing damage, and discuss the variety of variables that must be considered under certain environmental and operating conditions. The study concludes with demonstrating how to generally apply frozen bearing damage in healthy bridge models to represent possible future damage states.

Selecting the right sensor locations is pivotal for the effectiveness of vibration-based damage detection as part of structural monitoring under unknown excitation. Traditional optimization criteria aim to increase the signal-to-noise ratio and information content carried by ambient vibrations, or to identify modal parameters with minimal uncertainty and optimal mode distinguish ability. None of the existing criteria appear to consider a relative decrease in material strength, although this is the decisive quantity for structural design, structural health, and thus safety. This paper fills this gap for stochastic subspace-based damage diagnosis methods. It introduces an optimization criterion that ensures that a minimum damage extent can be detected in each structural component while maintaining a probability of detection that meets the national design standards. The presented strategy helps to find an acceptable number of sensors as well as their optimal layout. Further advantages are that the optimization can be done based on the simulated vibration data from the healthy structure and that the criterion can be tuned so the resulting sensor layout becomes more sensitive to damage hotpots.

Train movements generate oscillations that are transmitted as waves through the track support system into its surroundings. The waves reaching nearby structures may cause distractions for humans and/or result in equipment malfunctions. Dynamic characteristics of surrounding media affect the level of vibrations experienced in nearby buildings. In this paper, the authors are presenting a finite element analysis study performed to assess vibration levels due to train movements in nearby subway tunnels. The closer subway tunnel is located at an average horizontal distance of 50 ft (15.2 m) from an existing office building. While the authors focus on assessing vibration levels at the foundations of the office building, a plane strain finite element model is created to simulate the tunnel, surrounding rock and the soil stratum above the rock layer. The loading function is modeled as a sinusoidal point source and simulations are run for sensitivity analysis.

This paper describes a series of ambient vibration tests and modal analysis conducted on Guayaquil Metropolitan Cathedral, located in Guayaquil, Ecuador. The Guayaquil Cathedral is composed of the reinforced concrete frames and masonry infills, constructed in mid 1920s. Modal response analysis was performed to identify the dynamic properties of the structure, including predominant natural frequencies and the corresponding mode shapes to support seismic assessment and upgrading of the Cathedral. The testing program consisted of several setups on different locations of the structure including the roof of the main building, towers, and the dome. Two series of sensors were used to carry out the vibration measurements: (1) Tromino® velocity/acceleration wireless sensors; and (2) Polytec® Laser Vibrometers. The sensors were placed on predetermined locations according to the test plan; The wireless sensors were located on top of the roof, along the height of the towers, and top of the dome whereas the Laser Vibrometers were reflected to the Diaphragms to study the flexibility and also to determine the modal frequencies of the Diaphragms. The computer program ARTeMIS version 4, was used to perform the system identification of the structure. The software allows to develop a 3D model of the structure and test points; the resulting mode shapes are displayed using this geometry. Two different techniques were used for modal identification: the Enhanced Frequency Domain Decomposition (EFDD) and the Stochastic Subspace Identification (SSI). These two modal identification techniques were used to cross-validate the results. The joint analysis of the signals measured in various strategic points of the structure made it possible to identify the modal configurations and the corresponding natural frequencies. As the results of this study, the vibration modes of the main building, towers and dome in translational and torsional directions, as well as the motions of the diaphragms were discussed. Also, the natural frequencies and corresponding dynamic mode shapes were presented.

In this paper, the accuracies of four well-established floor vibration evaluation methods developed over the last couple of decades are investigated by comparing predictions with observed acceptability of each bay. A large database of steel-framed floors subjected to walking excitation is used for the evaluations and comparisons. Detailed comparisons have been made among the methods of the American Institute of Steel Construction (AISC) Design Guide 11 Chapter 4 Method; Steel Construction Institute (SCI) P354 Simplified Method; Steel Construction Institute (SCI) P354 Vibration Dose Values; and Human Induced Vibration of Steel Structures (HIVOSS) Method. The floor bay database is based on data collected from real buildings and it contains 22 satisfactory and 28 unsatisfactory bays, a total of 50 bays.

With the advent of lighter floor systems and the drive to lower the embodied energy in structures, meeting vibration serviceability requirements for floor systems can be a challenge. A number of guidelines have been published in the UK over the past 15 years (e.g. SCI P345, CCIP-016) that have been helpful in providing a consistent methodology. Although these can differ slightly in the detail, they are essentially based around the concept of response factor. Other methodologies have been proposed in continental Europe. The better documented one is the One-Step RMS90 (OS-RMS90) developed as part of the Technical Steel Research of the European Commission (e.g. EUR 24084 EN). Although similar in spirit, OS-RMS90 differs from the UK methodologies in key aspects which can be categorized along three strands (1) Footfall force definition, (2) Floor modelling and estimation of the dynamic response of the floor; (3) Acceptability criteria. This paper proposes a detailed comparison between these methodologies in each of these aspects and concludes by applying the methods on a composite floor case study. Based on this comparison, the merits of various quick assessments are evaluated.

Vibration-based structural health monitoring and damage detection has been long pursued as a multi-hazard tool for performance assessment and management of civil infrastructure. However, the majority of full-scale case studies have focused on the efficacy of vibration-based condition assessment to detect, localize, and quantify structural damage resulting from either overload or long-term deterioration mechanisms. To supplement the limited case studies of vibration-based condition assessment performed on fire damaged structures, experimental measurements obtained from a prestressed concrete parking deck following a large fire in an attached timber framed structure are presented. Experimental modal analysis was conducted on two elevations of prestressed concrete double tees in the parking deck using a stationary pair of shakers and a large array of uniaxial accelerometers. The two floor elevations were nominally identical in design, with one elevation featuring visible symptoms of localized fire damage across a portion of the span and the other exhibiting no visible evidence of fire damage. Impact echo testing was also performed on select double tees at each elevation to estimate reductions in the modulus of elasticity along the stems of each member. Coupled with camber measurements and visual condition surveys, the impact echo results are used to quantify the severity of the effects of the elevated temperatures on the double tees independent of the vibration-based condition assessment. Experimental estimates of the natural frequencies, damping ratios, and mode shapes for each elevation are developed and compared to illustrate empirical evidence of localized structural damage in the modal parameters of the elevation affected by the fire. The results suggest that the changes in experimental modal parameters resulting from fire damage are distinct from those typically associated with fracture or other localized forms of structural damage resulting from overload or deterioration and may necessitate the development of unique strategies specific to fire damage within multi-hazard structural health monitoring applications.

In this paper, we characterize the effects of obstructions on footstep-induced floor vibrations to enable obstruction-invariant indoor occupant localization. Occupant localization is important in smart building applications such as healthcare and energy management. In prior works, footstep-based vibration sensing has been introduced for non-intrusive occupant localization in open areas. However, real buildings have various types of obstructions (e.g., walls, furniture, etc.) which affect the wave propagation characteristics and significantly reduce localization accuracy. Requiring unobstructed paths between footsteps and sensors results in higher instrumentation and maintenance cost for these prior works. We have observed that the obstruction mass is one of the key factors affecting localization accuracy by altering wave propagation velocity. Therefore, to overcome the obstruction challenge, we (1) detect and estimate the mass of the obstruction by characterizing the attenuation rate, and (2) model the velocity-mass relationship to find the propagation velocities which in turn are used for occupant localization through non-isotropic multilateration. In field experiments, we achieved an average localization error of 0.61 m, which is a 1.6X improvement compared to the baseline approach.

Pedestrian-induced vibrations have caused significant issues on various footbridges, over the past few decades, as it can lead to an abrupt growth in the amplitude of structural oscillations, i.e. lateral dynamic instability. Measurements were taken during two separate crowd loading events on the Clifton Suspension Bridge, UK, to characterise the human-structure interactions observed. Two lateral modes of the bridge were studied, previously found susceptible to pedestrian-induced excitation. A comparative study is performed to identify the different interactions observed for the differing bridge deck amplitude responses through a novel procedure based on time-frequency analysis. This enables the identification of the fluctuations on the instantaneous modal amplitude and resonant frequency during pedestrian loading. Previous measurements of Clifton Suspension Bridge during crowd loading leading to the onset of large-amplitude vibrations revealed a significant increase in the natural frequency of the two modes considered. The instantaneous frequency, of both modes, appeared to roughly mirror the displacement amplitude response during significant loading, >250 pedestrians. Recent measurements of Clifton Suspension Bridge during crowd loading, illustrated tentative evidence for the presence of human-structure interactions during low-amplitude responses. For high amplitude responses on the bridge the modal frequencies were observed to increase with an increase in amplitude displaying a complex non-linear hardening effect for the two modes of vibration.

Large ancillary structures (e.g., traffic lights, light poles, signage structures) are prone to unusual or extreme dynamic behavior, especially during high winds events. The associated risks of fatigue failure and distractions to drivers require long-term dynamic monitoring solutions. Some of the major obstacles to wide-spread deployment are that traditional wired methods require lengthy lane closures, extensive data storage, and may measure only a single axis of vibration. This motivates the need for alternatives that are both easy to deploy and intuitive to interpret. The accuracy of the Embedor Technology XNode Smart Sensor for these purposes was studied using a 20-foot cantilevered traffic pole in the Thomas M. Murray Structures Lab at Virginia Tech. A double integrating and filtering approach was tested to estimate displacement from the acceleration readings and found to have a maximum uncertainty of one eighth of an inch when compared to a laser displacement sensor. The XNode’s ability to integrate other hardware, perform data processing on the edge, communicate on its own wireless network and provide accurate displacement estimates has potential to unseat the current state of the art for dynamic monitoring of ancillary traffic structures.

It is sometimes necessary to locate the source of machinery-induced vibrations in buildings when the generated vibration exceeds the acceptable limits. The objective of this study is to localize stationary source of vibration using floor vibration measurements with the steered response power (SRP) method. While this method has been used in microphone array processing and acoustic imaging systems, this paper describes the first application of this method to surface wave vibrations in structures. Source locations are derived from shifted and summed version of received signals by accelerometers to search and find the maximum likelihood of source location. Similar to the time difference of arrival (TDOA) method, the accuracy of the estimate is degraded by the frequency dependent propagation speed and attenuation of concrete floor, which lead to changes in the shape of the received signals. However, the SRP method is more robust than TDOA. Additional processing steps will be applied to reduce the effect of the aforementioned issues. The accuracy of the SRP method is validated through series of experiments in a building. To estimate the wave propagation speed, which is needed for SRP method, cross-correlation is used to compute delays between received signals. The accuracy of this method depends on the location of the source on the bay. Experiments showed an average error of 1 m or less for a single bay with a size of approximately 13.4 by 8.2 m when the source is located at mid bay. The results for SRP method as well as its advantages and shortcomings are discussed.

Prior to erecting a footbridge it may be useful to quantify the future and to predict vibration levels of the footbridge, since the vibration levels to come will determine the serviceability of the bridge throughout its service life. For design stage predictions of pedestrian-generated vibrations of a footbridge, decisions need to be made in terms of how to model the load. If the load is modelled as being stochastic it entails that a set of walking parameters are to be modelled as random variables for the predictions. Fundamentally, walking parameters are load amplification factors, step frequency, walking speed, pedestrian weight etc. and the paper adapts this line of thinking and presents results in terms of footbridge vibration levels computed under various calculation assumptions. Since the studies treat walking parameters as random variables, it is the stochastic nature of footbridge vibrations, which is in focus when comparing vibrations. The stochastic nature is brought about by Monte Carlo simulations, and a central aim of the studies of the paper is to examine how two different load models perform in terms of predicting selected stochastic features of footbridge vibrations when subjected to single-person traffic.

In recent years, Structural Health Monitoring (SHM) has gained a lot of attention, given the need to detect a structure damage at an early stage. A series of technological advances, especially in the world of new sensors, has allowed more structures to be equipped with an always increasing number of monitoring systems of different nature. The state of the art of monitoring systems involves the interaction and cooperation of elements such as low-cost sensors, efficient communication networks, data transfer and storage, often based on cloud architectures.

If on the one hand the amount of data collected by the new SHM systems tends to be of considerable size, the search for damage passes through a process of information synthesis aimed at defining features able to describe the health of the monitored structure.

Although many papers in literature are focused on the definition of an early warning through the most suitable damage feature, less attention has been paid till now to the challenge of implementing a fully automatic monitoring system that can serve as a robust and reliable tool for decision making.

This paper presents a framework/architecture for a real-time data elaboration process, based on different alarm levels to track an ongoing and growing damage. Into details, data coming from a large number of MEMS accelerometers, installed on tensioning cables inside a box composite highway bridge, are continuously processed and analyzed at the sensor level. This is done on a microcontroller equipping each sensor, thanks to both fit-to-the-purpose algorithms that do not require huge computational effort and a strategy which can manage each sensor independently from the others.

At a first stage, the proposed strategy is able to identify every kind of anomalies in the collected data; then, the benign phenomena, such as the occurrence of heavy though not extraordinary loading conditions, are identified and separated from those which clearly point at a damage, such as the breaking of the strands of prestressed cables. As these events occurred during the monitoring and have been recorded, we have a check about the capability of the chosen algorithms to perform this clustering.

Different output examples are discussed in this paper in order to provide a significant case study where the effectiveness of a SHM system is discussed in a damage detection perspective.

The aging of materials, combined with the persistence and alteration of both operational loads and atmospheric conditions, cause a decrease of the structural properties of civil structures. This raises questions of considerable importance when it comes into play the safety of infrastructure users, mainly related to bridges and roads. Therefore, monitoring and evaluating the health of such structures becomes of central importance, allowing a more efficient maintenance, aimed at preserving or recovering the required structural properties.

This article describes a case study where a structural health monitoring system has been installed on a damaged operating bridge, where the signs of heavy wear were first detected through visual inspections. Therefore, a network of accelerometers has been designed and installed to the purpose of monitoring the evolution of deterioration phenomena and testing some new approaches related to the use of MEMS sensors. In particular, sensors readings were collected in real-time in order to gain useful information about the dynamic behavior of the structure under ambient and traffic loads.

Data obtained from the monitoring system were used to support the decision of carrying out maintenance operations aiming at reinforcing the bridge, increasing its structural stiffness.

This result was achieved through the post tensioned reinforcement of the bridge, by means of external tendons. The vibration data were collected at different points along the bridge, before and after the maintenance operations, so that both the damaged and undamaged information are now known, suggesting a supervised learning approach for future monitoring of the structure.

The modal parameters of the bridge, extracted from the data, have been used to verify the change in structural stiffness, confirming the effectiveness of the adopted intervention in improving the structural property.

Dynamic properties (e.g. frequency and damping ratio) play an important role in determining the impact of natural disasters on tall buildings. A variety of system identification (SID) techniques have been developed and implemented on response measurement data from full-scale structures for condition assessment, where modal parameters were used as the condition indicators. Previous research has demonstrated the strengths and limitations of the Random Decrement Technique (RDT) as a time-domain SID technique. In this paper, the Time-Varying Filtering based Empirical Mode Decomposition (TVF-EMD), a new time-frequency-domain analysis method, is used on a suite of synthetic building response data to demonstrate how the RDT results can be further improved in lieu of bandpass filtering. The two techniques are then used together to extract the dynamic properties from a full-scale tall building and the results are compared against the use of bandpass filtering. It can be observed that RDT alone or in conjunction with an appropriate filter design is able to extract damping better in most cases. The current results suggest that TVF-EMD may provide accurate results but only if the noise level is low. On the other hand, the bandpass filtering only works better with appropriate filter design.

Main shaft thrust bearing failures are a major source of unplanned maintenance and downtime for wind turbines. Turbines are typically designed to operate for at least a 20-year lifetime, but the variable-amplitude loading of changing wind conditions promotes a high rate of early bearing failure, requiring maintenance work and increasing the cost of energy. The monitoring of bearing loading conditions plays a crucial role in determining design parameters and optimizing bearing life. It can also play a significant role in estimating the remaining lifetime of bearings, enabling the repair or replacement of these components before failure occurs, or in extending bearing lifetimes for existing turbines. In this study, a method for monitoring axial loading in the main shaft bearing is suggested using strain sensor data on the blades. The method is based on using the available strain time history measurements at the base of the three blades to calculate the internal forces andmoments in the main shaft. The method is implemented using data from a Clipper C96 Liberty wind turbine instrumented with interferometric strain sensors placed at the blade roots. The forces and moments acting on each blade are calculated using the data collected from the sensors. Through a rigid body equilibrium analysis, the resultant forces and moments acting on the main shaft bearing of the wind turbine are found. This data, in conjunction with SCADA data, is used to analyze the effect of strong and weak wind events on the fatigue life of the main shaft bearing. Results show that the method can be used to successfully identify wind conditions which produce axial forces beyond the bearing design assumptions.

Tracking occupants indoors has important applications such as intruder detection and tracking. It has been shown that a vibration measurement system of underfloor accelerometer sensor network can detect, localize, and track occupants in a non-intrusive manner. In the literature, little attention has been given to studying the problem of detecting occupant foot-fall impacts in a real-life scenario, and its effect on footstep impact localization, especially in the case of multiple occupants walking on the same instrumented area. Therefore, in this paper, a footstep detection algorithm is proposed and analyzed. The performance of the proposed algorithm is evaluated using occupant walking experiments on an instrumented floor section, inside an operational smart building. Additionally, the detected footsteps are localized using an energy-based localization method. Footstep detection and localization performances are compared between single occupant and multiple occupant cases.

In comparison, a salient motivation for implementing a structural health monitoring (SHM) system is to facilitate the decision-making process throughout the lifetime of a structure. Oftentimes, there is uncertainty when assessing the damage state of a structure. As such, a statistical pattern recognition (SPR) approach to structural health monitoring is employed in which data acquired from a structure of interest are processed to yield features indicative of the damage state. The current paper details how decision-making under uncertainty can be aided by augmenting the established structural health monitoring paradigm to incorporate risk, utilising a framework based on probabilistic graphical models.

The modelling of failure events as fault trees is a core process in conducting a PRA and, by modelling key failure modes of interest for a given structure in this way, provides a convenient and rigorous basis for formulating risk-based SHM problems. As statements in Boolean logic, fault trees are limited to representing binary damage states. Fortunately, it is possible to map fault trees into Bayesian networks which are capable of representing multi-state variables whilst also affording other benefits.

Risk is incorporated into the framework by introducing utility nodes into the probabilistic graphical model, thereby attributing costs to failure events. Decision nodes are also included, enabling the evaluation of potential courses of action such that a strategy that maximises utility may be determined.

The open-deck steel plate girder bridge in service has been an issue due to noise and vibration as well as its damage-prone structural characteristics of direct connection between a bridge beam and a track panel. Recently in Korea, to cope with the issue, a more economical method of installing CWR (Continuous Welded Rail) is being conducted using a stiffer sleeper-beam fastener installation, appropriate support arrangement and bridge substructure reinforcement. In this paper, using the finite element multibody dynamic analysis technology, running safety analysis is conducted considering track irregularities, and the appropriateness of the current track geometry standards is reviewed. The dynamic analysis is performed using commercial programs, ABAQUS and VI-Rail. A 30 m long open-deck plate girder bridge is utilized in the analysis. From the analysis, it is observed that the modification of the current geometry standard on track irregularities needs be considered.

Rotational inertia dampers have been proposed as passive vibration absorbers. Traditional rotational inertia dampers come in different configurations, but all feature a mechanical device called an inerter. The inerter is a two terminal device that can produce a large effective mass via the transformation of translational motion to the rotation of a flywheel. Despite the effectiveness of rotational inertia dampers at reducing the response of structures, there use has potential drawbacks. The inerter increases the effective mass of a system and, therefore, reduces the natural frequencies of that system; this shift in natural frequency is not always desirable. Furthermore, energy that is transferred to the inerter as rotational kinetic energy is transferred back to the structure when the structure’s motion slows, which can drive the response of the structure. To address these issues, one-way rotational inertia dampers have recently been proposed and investigated. In the one-way rotational damper, energy is transferred to a flywheel as rotational kinetic energy in a manner in which it cannot transfer back to the structure. In addition, the one-way rotational damper is not always engaged with the structure; thus, the effective mass of the system changes during its response. Due to these changes, also known as state-switching, it is not straightforward to evaluate the response of the system or its effective frequency. In this study, the effect of the one-way rotational inertia damper on the frequency and response of the base structure is investigated with numerical analyses.

One of the requirements of the population-based approach to Structural Health Monitoring (SHM) proposed in the earlier papers in this sequence, is that structures can be represented by points in an abstract space. Furthermore, these spaces should be metric spaces in a loose sense; i.e. there should be some measure of distance applicable to pairs of points; similar structures should then be ‘close’ in the metric. This geometrical structure is not enough for the framing of problems in data-based SHM, as it leaves undefined the notion of feature spaces. Interpreting the feature values on a structure-by-structure basis as a type of field over the space of structures, it seems sensible to borrow an idea from modern theoretical physics, and define feature assignments as sections in a vector bundle over the structure space. With this idea in place, one can interpret the effect of environmental and operational variations as gauge degrees of freedom, as in modern gauge field theories. One can then regard data normalisation procedures like cointegration as gauge-fixing operations. This paper will discuss the various geometrical structures required for an abstract theory of feature spaces in SHM, and will draw analogies with how these structures have shown their power in modern physics.

In this study, the modal parameters of a hallway floor in Goodwin Hall are compared with experimental modal analysis (EMA) and operational modal analysis (OMA). A set of 17 high sensitivity accelerometers mounted to structural beams under the floor of the hallway will be used to measure the floor response. In EMA an instrumented hammer was used to measure the input, while in OMA ambient excitation was used to excite the floor. The natural frequency, damping ratio, and mode shape estimates for the first five modes of the floor will be compared between the two methods. Despite limitations with generating enough energy to excite standing waves, the modal parameters between EMA and OMA match well. Frequency differences are less than 10%, and all the damping ratio estimates between 2% and 10%. Mode shapes also match well visually, and the MAC shows agreement between methods. Both EMA and OMA show the ability to extract modal parameters from the floor, where the mode shapes show global motion of the floor instead of only local motion between supports.

Live loads on structures such as dance halls, fitness centers, and malls can generate excessive vibrations causing serviceability problems. Several models were used to model force generated by human jumping on a flexible structure such as semi-sinusoidal pulse force, Fourier series, statistical model of the dynamic loads, and pseudo-variable mass models. While these models area able to represent the dynamics of the system in some cases, the human body is a more complex dynamic system. For example, Fourier series model and even other mentioned models are not capable to consider an external excitation like music sound as input to the overall system. This paper expands a prior model of human standing on flexible structure using control theory to a model that consider sound as the excitation to the human-structure system. Energy is added to the system when a person jump or performing short movement up and down at the bit of a metronome. Here, the sound created by the metronome is used as input to overall system.

A flexible cantilever structure, idealized as single degree of freedom system, is used to develop and validate the proposed model. The force exerted by people jumping as well as the acceleration records are used to determine the probability distribution functions of the model parameters. The model is validated by comparing model predictions with additional experimental records.

Ground-borne vibrations from roadway traffic are a common source of disturbance in urban areas. These vibrations are often due to poor road conditions combined with heavy vehicle movements near the receiving structure. Mitigation of vibration disturbances in existing structures usually requires a combination of added mass, added stiffness, and/or added damping to limit vibrations to acceptable levels. The suitability and feasibility of solutions will largely depend on site conditions, performance, and cost.

This paper presents a case study on control of traffic-induced ground motion disturbances in a historic residential structure. The building was previously occupied by commercial space but was known to have lively floors subjected to perceptible levels of motion induced by vehicle movements on the adjacent roadway. The desire of the owners to convert the commercial space to residential use raised concerns regarding impacts of traffic on comfort in the home. To assist with the renovation, the authors were engaged to investigate the problem and develop solutions for control. Site testing was completed to quantify existing vibration levels and structural dynamic properties. This was followed by an investigation of solutions including structural retrofits, passive dampers, and active control. Ultimately the owner proceeded with structural retrofits and following the renovation there was opportunity to complete performance measurements for verification of the solution.